Burden of schizophrenia on selected comorbidity costs
Bibliographic record
Abstract
Patients suffering from schizophrenia tend to have high rates of medical comorbidities and mortality.This study evaluated the healthcare costs of patients with schizophrenia and specific comorbidities relative to patients without schizophrenia with the same comorbidities, using Medicaid insurance claims databases from five states (from 2001-2010). The most common comorbidities were hypertension (48.8%), substance abuse (39.1%) and diabetes (28.4%). Patients with schizophrenia incurred greater all-cause monthly healthcare costs (cost difference [95% CI]: US$978 [933; 1024]) and comorbidity-related costs (cost difference [95% CI]: US$288 [269; 307]). Schizophrenia was also associated with significantly higher comorbidity-related costs in each comorbidity subgroup (among the three most common comorbidities: 99% higher in hypertension, 293% in substance abuse, and 105% in diabetes). The results suggest that patients with schizophrenia and comorbidities common in patients with schizophrenia had higher all-cause and comorbidity-related healthcare costs compared with patients without schizophrenia with the same comorbidities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".